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I will come round and register you individually

(it helps me learn your names)

This module

This module will equip you with the knowledge and skills to use maps to understand why crime happens in some places more than others

… and …

This module will introduce you to using R to analyse crime

Another programming language!? 😱

Why?

Three cute fuzzy monsters adding spatial geometries to an existing table of attributes using glue and tape, while one cuts out the spatial polygons. Title text reads “sf: spatial data...simplified.” and a caption at the bottom reads “sticky geometries: for people who love their maps and sanity.”

Different languages have different strengths

Python logo R logo

Knowing multiple languages gives you access to more jobs

Another programming language!?

You’ll also use R again:

  • Year 2: SECU0013 Probability, Statistics and Modelling II
  • Year 3: SECU0050 Data Science

A typical week

Monday–Thursday
work through chapters

Wednesday
in-person lecture and workshop

Friday
write and submit code for weekly practice exercise

Week by week

First half of term

Week Topic
1 Getting started
2 Wrangling data
3 Mapping crime patterns
4 Adding context to maps
5 Assessment 1

Second half of term

Week Topic
6 Using area data
7 Mapping hotspots
8 Mapping crime series
9 Mapping change over time
10 Assessment 2

After Easter: final assessment

Module assessment

Weight Deadline You will produce …
1 20% Wed 12 February (Week 5) Code to make 3 maps
2 20% Wed 26 March (Week 10) Code to make a short report
3 60% Thu 24 April (Term 3) Code to make a longer report

How to do well

Manage your time
don’t try to do it all in the in-person session

Complete all the activities
the lectures only cover part of what you need to know for the assessments

Ask lots of questions
easier to do in person than on Moodle

Practice
submit each week’s exercise before Friday @ 4pm

Module resources

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